Optimized viewport‐adaptive 360‐degree video streaming

Abstract

Because of the rapid growth of head-mounted displays and 5G networking deployment, 360-degree video has become increasingly popular. To generate the real experience of a virtual environment, 360-degree videos require an ultrahigh resolution and frame rate to cover an omnidirectional view. These two prerequisites impose challenges for the transmission bandwidth and storage capacity of 360-degree video streaming. To reduce bandwidth and storage waste while providing a good immersive experience, we propose an optimized viewport-adaptive 360-degree video streaming method using high-efficiency video coding tiling, motion-constrained tile sets and MPEG dynamic adaptive streaming over HTTP spatial relationship description. The paper describes the rigorous design of the optimized system, which can assign different bitrates to different tiles in the viewport. The experimental results show that the proposed streaming system compares favourably with existing methods in terms of bitrate savings and storage capacity reduction. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Dynamic Viewport Selection-Based Prioritized Bitrate Adaptation for Tile-Based 360° Video Streaming

“…Chen et al [6] introduced different priority levels within the viewport, i.e., the highest priority for the center tile, medium priority for the top, bottom, left, and right tiles, and the lowest priority for the four diagonal neighbor tiles. Different encoding versions or non-uniform quality levels are assigned to the viewport tiles (Fig.…”

“…The ever-increasing immersive real-time rendering [2] causes tremendous bandwidth consumption since the entire captured content, including the visible and non-visible scenes, has to be downloaded in higher resolution (≥8k) [3], [4]. Viewport-adaptive streaming is a straightforward approach to reduce the transmission bandwidth, where the quality of the scenes is dynamically adjusted in real-time depending on the user's Field-of-View (FoV) [5], [6]. Among viewport-based solutions, tile-based adaptive streaming is now a widely embraced solution to support transmitting quality-variable tiles without sacrificing visual quality in response to the user's interaction.…”

“…Existing techniques struggle to perform reliable viewport prediction, streaming tiles selection, and spatial and temporal bitrate adaptations. A straightforward technique is to predict viewpoint based on a single prediction mechanism and then calculate the viewing area by mapping the tiles to the horizontal and vertical lengths of the viewport as adopted in [6]- [10]. Such solutions work reasonably well under 1s segment duration with an accuracy of 58∼80% [11], [12].…”

“…The proposed solutions provide support for improved streaming tiles selection and bitrate adaptation based on content complexity and user engagement. Existing works [6]- [10], [15]- [17] only consider the viewing information to perform relevant tiles selection. Unlike these schemes, DVS solutions include content information as well as viewing behaviors to proactively select the streaming regions.…”

Lightweight Neural Network-Based Viewport Prediction for Live VR Streaming in Wireless Video Sensor Network

“…e 360-degree camera captures the panoramic video and delivers the streaming to the server. On the server side, the video is divided into segments by the packer, and then, they are distributed to the client through the content distribution network (CDN) using the optimized viewportadaptive 360-degree video streaming mechanism [25]. To reduce the bandwidth, the part inside the predicted viewport is coded with high quality, and the part outside the predicted viewport is coded with low quality [26][27][28][29].…”